Organizations around the world are considering the implications of pay transparency and pay equity regulations that result in fair and equitable employee compensation structures. The increasing expectation for employers to be better at rewards management requires compensation and HR professionals to provide objective reasons for pay differences among “like” employee categories.
While perhaps not the most glamorous work, job evaluations are a necessary step in designing and delivering fair compensation structures that are transparent and in-line with government-issued requirements, whether they be for a region, a state or a local government.
For example, the EU Pay Transparency Directive sets clear standards: Work of equal value must be evaluated in a gender-neutral and objective way (e.g., based on skills, effort and responsibility). In practice, compensation and HR professionals face considerable challenges:
- Too many jobs. Continued job code evaluations and new job requests.
- Too little time. The Directive takes effect in June 2026, less than a year away.
- Too few resources. HR teams are, for the most part, working at capacity.
Factor-based job evaluation methods provide differentiated and reliable results. However, they also are time-consuming and resource intensive. By leveraging the power of AI, organizations can harness a fast, efficient and replicable process for job evaluations.
AI-supported job evaluation in practice
WTW has been working with global clients to pilot AI-supported job evaluations. After nearly two years of conducting this pilot, we have found that the software has added value in three specific areas.
AI as a strategic HR partner
As these short examples show, AI can do far more than only save time. Developed and used the right way, an AI-based job evaluation system ensures:
- Objectivity: Uniform evaluations based on clear factors, independent of subjective assessments
- Market perspective: Based on thousands of job descriptions, the AI tool recognizes typical market standards, providing a valuable comparison with internal assessments
- Replicability: The same input leads to the same results, regardless of the mindset of the evaluator
- Quality control: The automated job leveling software delivers tips for improving job descriptions and supports role clarification
AI-supported job evaluation doesn’t replace human expertise; rather, it complements it in a meaningful way. The “human in the loop” will continue to be indispensable, but leveraging AI will provide a quick, objective and market-compliant support. In turn, compensation and HR professionals will see their time freed to focus on more meaningful, strategic work to support defensible employee pay decisions.
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